Name

montez

Megathread covering physical robotics across manufacturing arms, humanoids, and other machines to assist with object design and engineering

montez

Megathread covering South American object makers covering architecture, industrial design, and product design.

Format should follow

Name

Credentials:
From:
Based:
Discipline:

Website:
Instagram:
X:
Other Links:

At least 1 image

montez

Google Gemma 4

Hugging Face: https://huggingface.co/collections/google/gemma-4
GitHub: https://github.com/google-gemma
Website: https://ai.google.dev/gemma/docs/core
Announcement: https://blog.google/innovation-and-ai/technology/developers-tools/gemma-4/, https://blog.google/innovation-and-ai/technology/developers-tools/introducing-gemma-4-12B/

Developer: Google DeepMind
Released: 26B A4B and 31B: April 2026 / 12B Unified: June 2026
Variants: 12B Unified, 26B A4B, 31B
Parameters: 12B Unified: 11.95B / 26B A4B: 25.2B total, 3.8B active / 31B: 30.7B
Context: 256,000 tokens
Architecture: 31B: Dense / 26B A4B: MoE, 8 active of 128 experts plus 1 shared / 12B: Unified encoder-free dense, multimodal input projected directly into the decoder
License: Apache 2.0
Modalities: 12B: Text + Image + Audio / 26B A4B and 31B: Text + Image
Runs on: Laptop, consumer GPU/workstation class
Formats: GGUF via Ollama/LM Studio, safetensors via Hugging Face, Docker
On disk: 12B: 7GB Q4, estimated / 26B A4B: 15GB Q4, estimated / 31B: 18GB Q4, estimated

montez

Google Gemma 4 Effective

Hugging Face: https://huggingface.co/collections/google/gemma-4
GitHub: https://github.com/google-gemma
Website: https://ai.google.dev/gemma/docs/core
Announcement: https://blog.google/innovation-and-ai/technology/developers-tools/gemma-4/

Developer: Google DeepMind
Released: April 2026
Variants: E2B, E4B
Parameters: E2B: 2.3B effective, 5.1B with embeddings / E4B: 4.5B effective, 8B with embeddings
Context: 128,000 tokens
Architecture: Dense, hybrid local sliding window + global attention, Per-Layer Embeddings for on-device efficiency
License: Apache 2.0
Modalities: Text + Image + Audio
Runs on: Smartphone, Laptop, Edge device
Formats: GGUF via Ollama/LM Studio, safetensors via Hugging Face
On disk: E2B: 1.4GB Q4, estimated / E4B: 2.7GB Q4, estimated

montez

PrismML Bonsai Image 4B

Hugging Face: https://huggingface.co/prism-ml/bonsai-image-binary-4B-mlx-1bit, https://huggingface.co/prism-ml/bonsai-image-ternary-4B-mlx-2bit
GitHub: https://github.com/PrismML-Eng/Bonsai-Image-Demo
Website: https://prismml.com
Announcement: https://prismml.com/news/bonsai-image-4b

Developer: PrismML
Released: May 2026
Parameters: 4B, transformer trunk
Architecture: MMDiT diffusion transformer, base architecture FLUX.2 Klein 4B, 25 blocks: 5 double-stream + 20 single-stream
Variants: Binary, 1-bit / Ternary, 2-bit
License: Apache 2.0
Modalities: Text-to-Image
Runs on: Smartphone, Laptop
Formats: MLX 1-bit, MLX 2-bit, Gemlite 1-bit/2-bit for CUDA, safetensors
On disk: Binary: 0.93GB transformer, 3.42GB total deployment payload / Ternary: 1.21GB transformer

montez

Qwen3.6

Hugging Face: https://huggingface.co/Qwen/Qwen3.6-27B, https://huggingface.co/Qwen/Qwen3.6-35B-A3B
GitHub: https://github.com/QwenLM/Qwen3.6
Website: https://qwen.ai/

Developer: Alibaba Cloud, Qwen team
Released: April 2026
Parameters: 27B / 35B total, 3B active
Context: 262,144 tokens, extensible to 1,010,000
Architecture: Dense / MoE, 256 experts, 8 routed + 1 shared active
License: Apache 2.0
Modalities: Text + Vision
Runs on: Laptop, 24GB+ unified memory minimum
Formats: GGUF, MLX 4-bit, community quantizations
On disk: 27B: 16GB Q4_K_M, estimated / 35B-A3B: 21GB Q4_K_M, estimated

montez

Sarah Jang

Credentials: Pratt Institute; Carnegie Mellon University
From: New York State
Based: Brooklyn, NY
Discipline: Industrial Design, Furniture

Website: https://sarahjang.me
Instagram: https://www.instagram.com/sjang_studio/

Youri

Youri tableware system by Sarah Jang

Myre Chair

Myre Chair by Sarah Jang

Minhwa Chair

Minhwa Chair by Sarah Jang

montez

Liquid AI LFM2-24B-A2B

Hugging Face: https://huggingface.co/LiquidAI/LFM2-24B-A2B
GitHub: https://github.com/Liquid4All/cookbook
Website: https://www.liquid.ai
Announcement: https://www.liquid.ai/blog/lfm2-24b-a2b

Developer: Liquid AI
Released: February 2026
Parameters: 24B total, 2.3B active
Context: 32,768 tokens
Architecture: MoE, 40 layers: 30 conv + 10 attention, 64 experts, top-4 routing
License: LFM Open License v1.0
Modalities: Text
Runs on: Laptop, 14GB+ unified memory minimum, 32GB+ recommended
Formats: GGUF Q4_K_M, Q5_K_M, Q6_K, safetensors, ONNX
On disk: 14.44GB Q4_K_M / 16.93GB Q5_K_M / 19.58GB Q6_K

montez

Liquid AI LFM2.5-VL-450M

Hugging Face: https://huggingface.co/LiquidAI/LFM2.5-VL-450M
Website: https://www.liquid.ai
Announcement: https://www.liquid.ai/blog/lfm2-5-vl-450m

Developer: Liquid AI
Released: April 2026
Parameters: 450M
Context: 32,768 tokens
Architecture: hybrid gated-convolution + grouped-query attention LM backbone, LFM2.5-350M, with SigLIP2 NaFlex 86M vision encoder
License: LFM Open License v1.0
Modalities: Text + Vision, bounding box / object detection support
Runs on: Smartphone, Laptop, Edge device
Formats: GGUF, ONNX, MLX 4-bit/5-bit/6-bit/8-bit/bf16, safetensors
On disk: 270MB Q4, estimated

montez

IBM Granite 4.1 3B

Hugging Face: https://huggingface.co/ibm-granite/granite-4.1-3b
GitHub: https://github.com/ibm-granite/granite-4.1-language-models
Announcement: https://huggingface.co/blog/ibm-granite/granite-4-1

Developer: IBM
Released: April 2026
Parameters: 3B
Context: 512,000 tokens
Architecture: dense decoder-only transformer
License: Apache 2.0
Modalities: Text
Runs on: Smartphone, 2GB at 4-bit, estimated, Laptop, Edge device
Formats: GGUF Q4_K_M, Q5_K_M, Q6_K, Q8_0, MLX/Core ML via conversion
On disk: 2.2GB Q4_K_M, estimated

administrators

Posts

Name

Google Gemma 4

Google Gemma 4 Effective

PrismML Bonsai Image 4B

Qwen3.6

Sarah Jang

Youri

Myre Chair

Minhwa Chair

Liquid AI LFM2-24B-A2B

Liquid AI LFM2.5-VL-450M

IBM Granite 4.1 3B

Member List